A new cascaded multilevel inverter topology with galvanic isolation
- Hasan, Mubashwar, Abu-Siada, Ahmed, Islam, Syed, Dahidah, Mohamed
- Authors: Hasan, Mubashwar , Abu-Siada, Ahmed , Islam, Syed , Dahidah, Mohamed
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Transactions on Industry Applications Vol. 54, no. 4 (2018), p. 3463-3472
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- Description: IEEE This paper presents a new compact three-phase cascaded multilevel inverter (CMLI) topology with reduced device count and high frequency magnetic link. The proposed topology overcomes the predominant limitation of separate DC power supplies, which CMLI always require. The high frequency magnetic link also provides a galvanic isolation between the input and output sides of the inverter, which is essential for various grid-connected applications. The proposed topology utilizes an asymmetric inverter configuration that consists of cascaded H-bridge cells and a conventional three-phase two-level inverter. A toroidal core is employed for the high frequency magnetic link to ensure compact size and high-power density. Compared with counterpart CMLI topologies available in the literatures, the proposed inverter has the advantage of utilizing the least number of power electronic components without compromising the overall performance, particularly when a high number of output voltage levels is required. The feasibility of the proposed inverter is confirmed through extensive simulation and experimentally validated studies.
- Authors: Hasan, Mubashwar , Abu-Siada, Ahmed , Islam, Syed , Dahidah, Mohamed
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Transactions on Industry Applications Vol. 54, no. 4 (2018), p. 3463-3472
- Full Text:
- Reviewed:
- Description: IEEE This paper presents a new compact three-phase cascaded multilevel inverter (CMLI) topology with reduced device count and high frequency magnetic link. The proposed topology overcomes the predominant limitation of separate DC power supplies, which CMLI always require. The high frequency magnetic link also provides a galvanic isolation between the input and output sides of the inverter, which is essential for various grid-connected applications. The proposed topology utilizes an asymmetric inverter configuration that consists of cascaded H-bridge cells and a conventional three-phase two-level inverter. A toroidal core is employed for the high frequency magnetic link to ensure compact size and high-power density. Compared with counterpart CMLI topologies available in the literatures, the proposed inverter has the advantage of utilizing the least number of power electronic components without compromising the overall performance, particularly when a high number of output voltage levels is required. The feasibility of the proposed inverter is confirmed through extensive simulation and experimentally validated studies.
A new data driven long-term solar yield analysis model of photovoltaic power plants
- Ray, Biplob, Shah, Rakibuzzaman, Islam, Md Rabiul, Islam, Syed
- Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
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- Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.
- Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
- Full Text:
- Reviewed:
- Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.
A new fuzzy logic approach for consistent interpretation of dissolved gas-in-oil analysis
- Abu-Siada, Ahmed, Hmood, Sdood, Islam, Syed
- Authors: Abu-Siada, Ahmed , Hmood, Sdood , Islam, Syed
- Date: 2013
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 20, no. 6 (2013), p. 2343-2349
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- Description: Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results however all these techniques rely on personnel experience more than analytical formulation. As a result, various interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. Furthermore, significant number of DGA results fall outside the proposed codes of the current based-ratio interpretation techniques and cannot be diagnosed by these methods. Moreover, ratio methods fail to diagnose multiple fault conditions due to the mixing up of produced gases. To overcome these limitations, this paper introduces a new fuzzy logic approach to reduce dependency on expert personnel and to aid in standardizing DGA interpretation techniques. The approach relies on incorporating all existing DGA interpretation techniques into one expert model. DGA results of 2000 oil samples that were collected from different transformers of different rating and different life span are used to establish the model. Traditional DGA interpretation techniques are used to analyze the collected DGA results to evaluate the consistency and accuracy of each interpretation technique. Results of this analysis were then used to develop the proposed fuzzy logic model.
- Authors: Abu-Siada, Ahmed , Hmood, Sdood , Islam, Syed
- Date: 2013
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 20, no. 6 (2013), p. 2343-2349
- Full Text:
- Reviewed:
- Description: Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results however all these techniques rely on personnel experience more than analytical formulation. As a result, various interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. Furthermore, significant number of DGA results fall outside the proposed codes of the current based-ratio interpretation techniques and cannot be diagnosed by these methods. Moreover, ratio methods fail to diagnose multiple fault conditions due to the mixing up of produced gases. To overcome these limitations, this paper introduces a new fuzzy logic approach to reduce dependency on expert personnel and to aid in standardizing DGA interpretation techniques. The approach relies on incorporating all existing DGA interpretation techniques into one expert model. DGA results of 2000 oil samples that were collected from different transformers of different rating and different life span are used to establish the model. Traditional DGA interpretation techniques are used to analyze the collected DGA results to evaluate the consistency and accuracy of each interpretation technique. Results of this analysis were then used to develop the proposed fuzzy logic model.
A new technique to measure interfacial tension of transformer oil using UV-Vis spectroscopy
- Abu Bakar, Norazhar, Abu-Siada, Ahmed, Islam, Syed, El-Naggar, Mohammed
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Islam, Syed , El-Naggar, Mohammed
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 22, no. 2 (2015), p. 1275-1282
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- Description: Interfacial tension (IFT) and acid numbers of insulating oil are correlated with the number of years that a transformer has been in service and are used as a signal for transformer oil reclamation. Oil sampling for IFT measurement calls for extra precautions due to its high sensitivity to various oil parameters and environmental conditions. The current used technique to measure IFT of transformer oil is relatively expensive, requires an expert to conduct the test and it takes long time since the extraction of oil sample, sending it to external laboratory and getting the results back. This paper introduces a new technique to estimate the IFT of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. UV-Vis spectral response of transformer oil can be measured instantly with relatively cheap equipment, does not need an expert person to conduct the test and has the potential to be implemented online. Results show that there is a good correlation between oil spectral response and its IFT value. Artificial neural network (ANN) approach is proposed to model this correlation.
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Islam, Syed , El-Naggar, Mohammed
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 22, no. 2 (2015), p. 1275-1282
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- Description: Interfacial tension (IFT) and acid numbers of insulating oil are correlated with the number of years that a transformer has been in service and are used as a signal for transformer oil reclamation. Oil sampling for IFT measurement calls for extra precautions due to its high sensitivity to various oil parameters and environmental conditions. The current used technique to measure IFT of transformer oil is relatively expensive, requires an expert to conduct the test and it takes long time since the extraction of oil sample, sending it to external laboratory and getting the results back. This paper introduces a new technique to estimate the IFT of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. UV-Vis spectral response of transformer oil can be measured instantly with relatively cheap equipment, does not need an expert person to conduct the test and has the potential to be implemented online. Results show that there is a good correlation between oil spectral response and its IFT value. Artificial neural network (ANN) approach is proposed to model this correlation.
A new topology for doubly fed induction generator to improve the overall performance of wind energy conversion system
- Khamaira, Mahmoud, Abu-Siada, Ahmed, Islam, Syed, Masoum, Mohammad
- Authors: Khamaira, Mahmoud , Abu-Siada, Ahmed , Islam, Syed , Masoum, Mohammad
- Date: 2014
- Type: Text , Journal article
- Relation: Elixir International Journal: Electrical Engineering Vol. 73, no. (2014), p. 26432-26435
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- Description: Doubly Fed Induction Generators (DFIGs) are currently extensively used in variable speed wind power plants due to their superior advantages that include reduced converter rating, low cost, reduced losses, easy implementation of power factor correction schemes, variable speed operation and four quadrants active and reactive power control capabilities. On the other hand, DFIG sensitivity to grid disturbances, especially for voltage sags represents the main disadvantage of the equipment. In this paper, a coil is proposed to be integrated within the DFIG converters to improve the overall performance of a DFIGbased wind energy conversion system (WECS). The charging and discharging of the coil are controlled by controlling the duty cycle of the switches of the dc-dc chopper. Simulation results reveal the effectiveness of the proposed topology in improving the overall performance of the WECS system under study.
- Authors: Khamaira, Mahmoud , Abu-Siada, Ahmed , Islam, Syed , Masoum, Mohammad
- Date: 2014
- Type: Text , Journal article
- Relation: Elixir International Journal: Electrical Engineering Vol. 73, no. (2014), p. 26432-26435
- Full Text:
- Reviewed:
- Description: Doubly Fed Induction Generators (DFIGs) are currently extensively used in variable speed wind power plants due to their superior advantages that include reduced converter rating, low cost, reduced losses, easy implementation of power factor correction schemes, variable speed operation and four quadrants active and reactive power control capabilities. On the other hand, DFIG sensitivity to grid disturbances, especially for voltage sags represents the main disadvantage of the equipment. In this paper, a coil is proposed to be integrated within the DFIG converters to improve the overall performance of a DFIGbased wind energy conversion system (WECS). The charging and discharging of the coil are controlled by controlling the duty cycle of the switches of the dc-dc chopper. Simulation results reveal the effectiveness of the proposed topology in improving the overall performance of the WECS system under study.
A novel concept for three-phase cascaded multilevel inverter topologies
- Hasan, Mubashwar, Abu-Siada, Ahmed, Islam, Syed, Muyeen, S.
- Authors: Hasan, Mubashwar , Abu-Siada, Ahmed , Islam, Syed , Muyeen, S.
- Date: 2018
- Type: Text , Journal article
- Relation: Energies Vol. 11, no. 2 (2018), p. 1-16
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- Description: One of the key challenges in multilevel inverters (MLIs) design is to reduce the number of components used in the implementation while maximising the number of output voltage levels. This paper proposes a new concept that facilitates a device count reduction technique of existing cascaded MLIs. Moreover, the proposed concept can be utilised to extend existing single phase cascaded MLI topologies to three-phase structure without tripling the number of semiconductor components and input dc-supplies as per the current practice. The new generalized concept involves two stages; namely, cascaded stage and phase generator stage. The phase generator stage is a combination of a conventional three-phase two level inverter and three bi-directional switches while the cascaded stage can employ any existing cascaded topology. A laboratory prototype model is built and extensive experimental analyses are conducted to validate the feasibility of the proposed cascaded MLI concept.
- Authors: Hasan, Mubashwar , Abu-Siada, Ahmed , Islam, Syed , Muyeen, S.
- Date: 2018
- Type: Text , Journal article
- Relation: Energies Vol. 11, no. 2 (2018), p. 1-16
- Full Text:
- Reviewed:
- Description: One of the key challenges in multilevel inverters (MLIs) design is to reduce the number of components used in the implementation while maximising the number of output voltage levels. This paper proposes a new concept that facilitates a device count reduction technique of existing cascaded MLIs. Moreover, the proposed concept can be utilised to extend existing single phase cascaded MLI topologies to three-phase structure without tripling the number of semiconductor components and input dc-supplies as per the current practice. The new generalized concept involves two stages; namely, cascaded stage and phase generator stage. The phase generator stage is a combination of a conventional three-phase two level inverter and three bi-directional switches while the cascaded stage can employ any existing cascaded topology. A laboratory prototype model is built and extensive experimental analyses are conducted to validate the feasibility of the proposed cascaded MLI concept.
A proximal subgradient algorithm with extrapolation for structured nonconvex nonsmooth problems
- Pham, Tan, Dao, Minh, Shah, Rakibuzzaman, Sultanova, Nargiz, Li, Guoyin, Islam, Syed
- Authors: Pham, Tan , Dao, Minh , Shah, Rakibuzzaman , Sultanova, Nargiz , Li, Guoyin , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: Numerical Algorithms Vol. 94, no. 4 (2023), p. 1763-1795
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- Description: In this paper, we consider a class of structured nonconvex nonsmooth optimization problems, in which the objective function is formed by the sum of a possibly nonsmooth nonconvex function and a differentiable function with Lipschitz continuous gradient, subtracted by a weakly convex function. This general framework allows us to tackle problems involving nonconvex loss functions and problems with specific nonconvex constraints, and it has many applications such as signal recovery, compressed sensing, and optimal power flow distribution. We develop a proximal subgradient algorithm with extrapolation for solving these problems with guaranteed subsequential convergence to a stationary point. The convergence of the whole sequence generated by our algorithm is also established under the widely used Kurdyka–Łojasiewicz property. To illustrate the promising numerical performance of the proposed algorithm, we conduct numerical experiments on two important nonconvex models. These include a compressed sensing problem with a nonconvex regularization and an optimal power flow problem with distributed energy resources. © 2023, The Author(s).
- Authors: Pham, Tan , Dao, Minh , Shah, Rakibuzzaman , Sultanova, Nargiz , Li, Guoyin , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: Numerical Algorithms Vol. 94, no. 4 (2023), p. 1763-1795
- Full Text:
- Reviewed:
- Description: In this paper, we consider a class of structured nonconvex nonsmooth optimization problems, in which the objective function is formed by the sum of a possibly nonsmooth nonconvex function and a differentiable function with Lipschitz continuous gradient, subtracted by a weakly convex function. This general framework allows us to tackle problems involving nonconvex loss functions and problems with specific nonconvex constraints, and it has many applications such as signal recovery, compressed sensing, and optimal power flow distribution. We develop a proximal subgradient algorithm with extrapolation for solving these problems with guaranteed subsequential convergence to a stationary point. The convergence of the whole sequence generated by our algorithm is also established under the widely used Kurdyka–Łojasiewicz property. To illustrate the promising numerical performance of the proposed algorithm, we conduct numerical experiments on two important nonconvex models. These include a compressed sensing problem with a nonconvex regularization and an optimal power flow problem with distributed energy resources. © 2023, The Author(s).
A review on chemical diagnosis techniques for transformer paper insulation degradation
- Abu Bakar, Norazhar, Abu Siada, Ahmed, Islam, Syed
- Authors: Abu Bakar, Norazhar , Abu Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 Australasian Universities Power Engineering Conference, AUPEC 2013; Hobart, Australia; 29th September-3rd October 2013 p. 1-6
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- Description: Energized parts within power transformer are isolated using paper insulation and are immersed in insulating oil. Hence, transformer oil and paper insulation are essential sources to detect incipient and fast developing power transformer faults. Several chemical diagnoses techniques are developed to examine the condition of paper insulation such as degree of polymerization, carbon oxides, furanic compounds and methanol. The principle and limitation of these diagnoses are discussed and compared in this paper.
- Authors: Abu Bakar, Norazhar , Abu Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 Australasian Universities Power Engineering Conference, AUPEC 2013; Hobart, Australia; 29th September-3rd October 2013 p. 1-6
- Full Text:
- Reviewed:
- Description: Energized parts within power transformer are isolated using paper insulation and are immersed in insulating oil. Hence, transformer oil and paper insulation are essential sources to detect incipient and fast developing power transformer faults. Several chemical diagnoses techniques are developed to examine the condition of paper insulation such as degree of polymerization, carbon oxides, furanic compounds and methanol. The principle and limitation of these diagnoses are discussed and compared in this paper.
Analysis of end-to-end delay characteristics for various packets in IEC 61850 substation communications system
- Das, Narottam, Ma, Wu, Islam, Syed
- Authors: Das, Narottam , Ma, Wu , Islam, Syed
- Date: 2015
- Type: Text , Conference proceedings , Conference paper
- Relation: 25th Australasian Universities Power Engineering Conference, AUPEC 2015, Wollongong, Australia; 27th-30th September 2015 p. 1-5
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- Reviewed:
- Description: Substation plays an important role in power system communications for safe and reliable operation of entire power networks. Substation communication networks are connected with various substation intelligent electronic devices (IEDs), which is substation systems lifeblood and the system availability is decided by its real-Time performance. International Electro-Technical Commission (IEC) has been developed the standards based on object-oriented technologies for substation automation. IEC 61850 protocol has been applied widely in substation communication applications. It presents new challenges to realtime performance simulation and testing of protective relays. In this paper, an optimized network engineering tool (OPNET) or Riverbed modeler simulation tool/ software has been used for the modeling of IED in substation level network. Based on the simulation results, different types of data stream have been discussed, such as, periodic data stream, random data stream and burst data steam. The typical studies using these models, to construct substation automation system (SAS) network on the OPNET modeler or Riverbed modeler was made to reveal the impact of each affecting parameter or factor to the real-Time performance of substation communications system, which is also incorporated in this report.
- Description: 2015 Australasian Universities Power Engineering Conference: Challenges for Future Grids, AUPEC 2015
- Authors: Das, Narottam , Ma, Wu , Islam, Syed
- Date: 2015
- Type: Text , Conference proceedings , Conference paper
- Relation: 25th Australasian Universities Power Engineering Conference, AUPEC 2015, Wollongong, Australia; 27th-30th September 2015 p. 1-5
- Full Text:
- Reviewed:
- Description: Substation plays an important role in power system communications for safe and reliable operation of entire power networks. Substation communication networks are connected with various substation intelligent electronic devices (IEDs), which is substation systems lifeblood and the system availability is decided by its real-Time performance. International Electro-Technical Commission (IEC) has been developed the standards based on object-oriented technologies for substation automation. IEC 61850 protocol has been applied widely in substation communication applications. It presents new challenges to realtime performance simulation and testing of protective relays. In this paper, an optimized network engineering tool (OPNET) or Riverbed modeler simulation tool/ software has been used for the modeling of IED in substation level network. Based on the simulation results, different types of data stream have been discussed, such as, periodic data stream, random data stream and burst data steam. The typical studies using these models, to construct substation automation system (SAS) network on the OPNET modeler or Riverbed modeler was made to reveal the impact of each affecting parameter or factor to the real-Time performance of substation communications system, which is also incorporated in this report.
- Description: 2015 Australasian Universities Power Engineering Conference: Challenges for Future Grids, AUPEC 2015
Assessing transformer oil quality using deep convolutional networks
- Alam, Mohammad, Karmakar, Gour, Islam, Syed, Kamruzzaman, Joarder, Chetty, Madhu, Lim, Suryani, Appuhamillage, Gayan, Chattopadhyay, Gopi, Wilcox, Steve, Verheyen, Vincent
- Authors: Alam, Mohammad , Karmakar, Gour , Islam, Syed , Kamruzzaman, Joarder , Chetty, Madhu , Lim, Suryani , Appuhamillage, Gayan , Chattopadhyay, Gopi , Wilcox, Steve , Verheyen, Vincent
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th Australasian Universities Power Engineering Conference, AUPEC 2019
- Full Text:
- Reviewed:
- Description: Electrical power grids comprise a significantly large number of transformers that interconnect power generation, transmission and distribution. These transformers having different MVA ratings are critical assets that require proper maintenance to provide long and uninterrupted electrical service. The mineral oil, an essential component of any transformer, not only provides cooling but also acts as an insulating medium within the transformer. The quality and the key dissolved properties of insulating mineral oil for the transformer are critical with its proper and reliable operation. However, traditional chemical diagnostic methods are expensive and time-consuming. A transformer oil image analysis approach, based on the entropy value of oil, which is inexpensive, effective and quick. However, the inability of entropy to estimate the vital transformer oil properties such as equivalent age, Neutralization Number (NN), dissipation factor (tanδ) and power factor (PF); and many intuitively derived constants usage limit its estimation accuracy. To address this issue, in this paper, we introduce an innovative transformer oil analysis using two deep convolutional learning techniques such as Convolutional Neural Network (ConvNet) and Residual Neural Network (ResNet). These two deep neural networks are chosen for this project as they have superior performance in computer vision. After estimating the equivalent aging year of transformer oil from its image by our proposed method, NN, tanδ and PF are computed using that estimated age. Our deep learning based techniques can accurately predict the transformer oil equivalent age, leading to calculate NN, tanδ and PF more accurately. The root means square error of estimated equivalent age produced by entropy, ConvNet and ResNet based methods are 0.718, 0.122 and 0.065, respectively. ConvNet and ResNet based methods have reduced the error of the oil age estimation by 83% and 91%, respectively compared to that of the entropy method. Our proposed oil image analysis can calculate the equivalent age that is very close to the actual age for all images used in the experiment. © 2019 IEEE.
- Description: E1
- Authors: Alam, Mohammad , Karmakar, Gour , Islam, Syed , Kamruzzaman, Joarder , Chetty, Madhu , Lim, Suryani , Appuhamillage, Gayan , Chattopadhyay, Gopi , Wilcox, Steve , Verheyen, Vincent
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th Australasian Universities Power Engineering Conference, AUPEC 2019
- Full Text:
- Reviewed:
- Description: Electrical power grids comprise a significantly large number of transformers that interconnect power generation, transmission and distribution. These transformers having different MVA ratings are critical assets that require proper maintenance to provide long and uninterrupted electrical service. The mineral oil, an essential component of any transformer, not only provides cooling but also acts as an insulating medium within the transformer. The quality and the key dissolved properties of insulating mineral oil for the transformer are critical with its proper and reliable operation. However, traditional chemical diagnostic methods are expensive and time-consuming. A transformer oil image analysis approach, based on the entropy value of oil, which is inexpensive, effective and quick. However, the inability of entropy to estimate the vital transformer oil properties such as equivalent age, Neutralization Number (NN), dissipation factor (tanδ) and power factor (PF); and many intuitively derived constants usage limit its estimation accuracy. To address this issue, in this paper, we introduce an innovative transformer oil analysis using two deep convolutional learning techniques such as Convolutional Neural Network (ConvNet) and Residual Neural Network (ResNet). These two deep neural networks are chosen for this project as they have superior performance in computer vision. After estimating the equivalent aging year of transformer oil from its image by our proposed method, NN, tanδ and PF are computed using that estimated age. Our deep learning based techniques can accurately predict the transformer oil equivalent age, leading to calculate NN, tanδ and PF more accurately. The root means square error of estimated equivalent age produced by entropy, ConvNet and ResNet based methods are 0.718, 0.122 and 0.065, respectively. ConvNet and ResNet based methods have reduced the error of the oil age estimation by 83% and 91%, respectively compared to that of the entropy method. Our proposed oil image analysis can calculate the equivalent age that is very close to the actual age for all images used in the experiment. © 2019 IEEE.
- Description: E1
Assessment of post-contingency congestion risk of wind power with asset dynamic ratings
- Banerjee, Binayak, Jayaweera, Dilan, Islam, Syed
- Authors: Banerjee, Binayak , Jayaweera, Dilan , Islam, Syed
- Date: 2015
- Type: Text , Journal article
- Relation: International Journal of Electrical Power and Energy Systems Vol. 69, no. (2015), p. 295-303
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- Reviewed:
- Description: Large scale integration of wind power can be deterred by congestion following an outage that results in constrained network capacity. Post outage congestion can be mitigated by the application of event control strategies; however they may not always benefit large wind farms. This paper investigates this problem in detail and proposes an advanced mathematical framework to model network congestion as functions of stochastic limits of network assets to capture post contingency risk of network congestion resulting through the constrained network capacity that limits high penetration of wind. The benefit of this approach is that it can limit the generation to be curtailed or re-dispatched by dynamically enhancing the network latent capacity in the event of outages or as per the need. The uniqueness of the proposed mathematical model is that it converts conventional thermal constraints to dynamic constraints by using a discretized stochastic penalty function with quadratic approximation of constraint relaxation penalty. The case study results with large and small network models suggest that the following an outage, wind utilization under dynamic line rating can be increased considerably if the wind power producers maintain around a 15% margin of operation.
- Authors: Banerjee, Binayak , Jayaweera, Dilan , Islam, Syed
- Date: 2015
- Type: Text , Journal article
- Relation: International Journal of Electrical Power and Energy Systems Vol. 69, no. (2015), p. 295-303
- Full Text:
- Reviewed:
- Description: Large scale integration of wind power can be deterred by congestion following an outage that results in constrained network capacity. Post outage congestion can be mitigated by the application of event control strategies; however they may not always benefit large wind farms. This paper investigates this problem in detail and proposes an advanced mathematical framework to model network congestion as functions of stochastic limits of network assets to capture post contingency risk of network congestion resulting through the constrained network capacity that limits high penetration of wind. The benefit of this approach is that it can limit the generation to be curtailed or re-dispatched by dynamically enhancing the network latent capacity in the event of outages or as per the need. The uniqueness of the proposed mathematical model is that it converts conventional thermal constraints to dynamic constraints by using a discretized stochastic penalty function with quadratic approximation of constraint relaxation penalty. The case study results with large and small network models suggest that the following an outage, wind utilization under dynamic line rating can be increased considerably if the wind power producers maintain around a 15% margin of operation.
Blockchain based smart auction mechanism for distributed peer-to-peer energy trading
- Islam, Md Ezazul, Chetty, Madhu, Lim, Suryani, Chadhar, Mehmood, Islam, Syed
- Authors: Islam, Md Ezazul , Chetty, Madhu , Lim, Suryani , Chadhar, Mehmood , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 55th Annual Hawaii International Conference on System Sciences, HICSS 2022, Virtual, online, 3-7 January 2022, Proceedings of the Annual Hawaii International Conference on System Sciences Vol. 2022-January, p. 6013-6022
- Full Text:
- Reviewed:
- Description: Blockchain based framework provides data immutability in a distributed network. In this paper, we investigate the application of blockchain for peer-to-peer (P2P) energy trading. Traditional energy trading systems use simple passing mechanisms and basic pricing methods, thus adversely affect the efficiency and buyers' social welfare. We propose a blockchain based energy trading mechanism that uses smart passing of unspent auction reservations to (a) minimise the time taken to settle an auction (convergence time), (b) maximise the number of auction settlement; and (c) incorporate second-price auction pricing to maximise buyers' social welfare in a distributed double auction environment. The entire mechanism is implemented within Hyperledger Fabric, an open-source blockchain framework, to manage the data and provide smart contracts. Experiments show that our approach minimises the convergence time, maximises the number of auction settlement, and increases the social welfare of buyers compared to existing methods. © 2022 IEEE Computer Society. All rights reserved.
- Authors: Islam, Md Ezazul , Chetty, Madhu , Lim, Suryani , Chadhar, Mehmood , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 55th Annual Hawaii International Conference on System Sciences, HICSS 2022, Virtual, online, 3-7 January 2022, Proceedings of the Annual Hawaii International Conference on System Sciences Vol. 2022-January, p. 6013-6022
- Full Text:
- Reviewed:
- Description: Blockchain based framework provides data immutability in a distributed network. In this paper, we investigate the application of blockchain for peer-to-peer (P2P) energy trading. Traditional energy trading systems use simple passing mechanisms and basic pricing methods, thus adversely affect the efficiency and buyers' social welfare. We propose a blockchain based energy trading mechanism that uses smart passing of unspent auction reservations to (a) minimise the time taken to settle an auction (convergence time), (b) maximise the number of auction settlement; and (c) incorporate second-price auction pricing to maximise buyers' social welfare in a distributed double auction environment. The entire mechanism is implemented within Hyperledger Fabric, an open-source blockchain framework, to manage the data and provide smart contracts. Experiments show that our approach minimises the convergence time, maximises the number of auction settlement, and increases the social welfare of buyers compared to existing methods. © 2022 IEEE Computer Society. All rights reserved.
Classifying transformer winding deformation fault types and degrees using FRA based on support vector machine
- Liu, Jiangnan, Zhao, Zhongyong, Tang, Chao, Yao, Chenguo, Li, Chengxiang, Islam, Syed
- Authors: Liu, Jiangnan , Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Li, Chengxiang , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 112494-112504
- Full Text:
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- Description: As an important part of power system, power transformer plays an irreplaceable role in the process of power transmission. Diagnosis of transformer's failure is of significance to maintain its safe and stable operation. Frequency response analysis (FRA) has been widely accepted as an effective tool for winding deformation fault diagnosis, which is one of the common failures for power transformers. However, there is no standard and reliable code for FRA interpretation as so far. In this paper, support vector machine (SVM) is combined with FRA to diagnose transformer faults. Furthermore, advanced optimization algorithms are also applied to improve the performance of models. A series of winding fault emulating experiments were carried out on an actual model transformer, the key features are extracted from measured FRA data, and the diagnostic model is trained and obtained, to arrive at an outcome for classifying the fault types and degrees of winding deformation faults with satisfactory accuracy. The diagnostic results indicate that this method has potential to be an intelligent, standardized, accurate and powerful tool.
- Authors: Liu, Jiangnan , Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Li, Chengxiang , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 112494-112504
- Full Text:
- Reviewed:
- Description: As an important part of power system, power transformer plays an irreplaceable role in the process of power transmission. Diagnosis of transformer's failure is of significance to maintain its safe and stable operation. Frequency response analysis (FRA) has been widely accepted as an effective tool for winding deformation fault diagnosis, which is one of the common failures for power transformers. However, there is no standard and reliable code for FRA interpretation as so far. In this paper, support vector machine (SVM) is combined with FRA to diagnose transformer faults. Furthermore, advanced optimization algorithms are also applied to improve the performance of models. A series of winding fault emulating experiments were carried out on an actual model transformer, the key features are extracted from measured FRA data, and the diagnostic model is trained and obtained, to arrive at an outcome for classifying the fault types and degrees of winding deformation faults with satisfactory accuracy. The diagnostic results indicate that this method has potential to be an intelligent, standardized, accurate and powerful tool.
Condition monitoring techniques of the wind turbines gearbox and rotor
- Salem, Abdulwahed, Abu-Siada, Ahmed, Islam, Syed
- Authors: Salem, Abdulwahed , Abu-Siada, Ahmed , Islam, Syed
- Date: 2014
- Type: Text , Journal article , Conference paper
- Relation: 6th International Conference on Computer and Electrical Engineering (ICCEE 2013); Paris, France; 30th-31st December 2013; published in International Journal of Electrical Energy Vol. 2, no. 1 (2014), p. 53-56
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- Description: Gearbox and the blades are classified as the most critical and expensive components of the wind turbine. Moreover, these parts are prone to high risk failure when compared to the rest of the wind turbine components. Due to the global significant increase in wind turbines, a reliable and cost effective condition monitoring technique is essential to maintain the availability and to improve the reliability of wind turbines. This paper aims to present a comprehensive review of the latest condition monitoring techniques for turbine gearbox and blades which are considered as the crux of any wind energy conversion system.
- Authors: Salem, Abdulwahed , Abu-Siada, Ahmed , Islam, Syed
- Date: 2014
- Type: Text , Journal article , Conference paper
- Relation: 6th International Conference on Computer and Electrical Engineering (ICCEE 2013); Paris, France; 30th-31st December 2013; published in International Journal of Electrical Energy Vol. 2, no. 1 (2014), p. 53-56
- Full Text:
- Reviewed:
- Description: Gearbox and the blades are classified as the most critical and expensive components of the wind turbine. Moreover, these parts are prone to high risk failure when compared to the rest of the wind turbine components. Due to the global significant increase in wind turbines, a reliable and cost effective condition monitoring technique is essential to maintain the availability and to improve the reliability of wind turbines. This paper aims to present a comprehensive review of the latest condition monitoring techniques for turbine gearbox and blades which are considered as the crux of any wind energy conversion system.
Contributions of single–phase rooftop PVs on short circuits faults in residential feeders
- Yengejeh, Hadi, Shahnia, Farhad, Islam, Syed
- Authors: Yengejeh, Hadi , Shahnia, Farhad , Islam, Syed
- Date: 2014
- Type: Text , Conference proceedings , Conference paper
- Relation: 24th Australasian Universities Power Engineering Conference, AUPEC 2014; Perth, Australia; 28th September-1st October 2014 p. 1-6
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- Description: Sensitivity analysis results are presented to investigate the presence of single–phase rooftop Photovoltaic Cells (PV) in low voltage residential feeders, during short circuits in the overhead lines. The PV rating and location in the feeder and the fault location are considered as the variables of the sensitivity analysis. The single–phase faults are the main focus of this paper and the PV effect on fault current, current in distribution transformer secondary and the voltage at each bus of the feeder are investigated, during fault. Furthermore, to analyze the bus voltages and fault current in the presence of multiple PVs, each with different rating and location, a stochastic analysis is carried out to investigate the expected probability density function of these parameters, considering the uncertainties of PV rating and location as well as fault location.
- Authors: Yengejeh, Hadi , Shahnia, Farhad , Islam, Syed
- Date: 2014
- Type: Text , Conference proceedings , Conference paper
- Relation: 24th Australasian Universities Power Engineering Conference, AUPEC 2014; Perth, Australia; 28th September-1st October 2014 p. 1-6
- Full Text:
- Reviewed:
- Description: Sensitivity analysis results are presented to investigate the presence of single–phase rooftop Photovoltaic Cells (PV) in low voltage residential feeders, during short circuits in the overhead lines. The PV rating and location in the feeder and the fault location are considered as the variables of the sensitivity analysis. The single–phase faults are the main focus of this paper and the PV effect on fault current, current in distribution transformer secondary and the voltage at each bus of the feeder are investigated, during fault. Furthermore, to analyze the bus voltages and fault current in the presence of multiple PVs, each with different rating and location, a stochastic analysis is carried out to investigate the expected probability density function of these parameters, considering the uncertainties of PV rating and location as well as fault location.
Design and analysis of nano-structured gratings for conversion efficiency improvement in GaAs solar cells
- Authors: Das, Narottam , Islam, Syed
- Date: 2016
- Type: Text , Journal article
- Relation: Energies Vol. 9, no. 9 (2016), p. 1-13
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- Description: This paper presents the design and analysis of nano-structured gratings to improve the conversion efficiency in GaAs solar cells by reducing the light reflection losses. A finite-difference time domain (FDTD) simulation tool is used to design and simulate the light reflection losses of the subwavelength grating (SWG) structure in GaAs solar cells. The SWG structures perform as an excellent alternative antireflective (AR) coating due to their capacity to reduce the reflection losses in GaAs solar cells. It allows the gradual change in the refractive index that confirms an excellent AR and the light trapping properties, when compared with the planar thin film structures. The nano-rod structure performs as a single layer AR coating, whereas the triangular (i.e., conical or perfect cone) and parabolic (i.e., trapezoidal/truncated cone) shaped nano-grating structures perform as a multilayer AR coating. The simulation results confirm that the reflection loss of triangular-shaped nano-grating structures having a 300-nm grating height and a 830-nm period is about 2%, which is about 28% less than the flat type substrates. It also found that the intermediate (i.e., trapezoidal and parabolic)-shaped structures, the light reflection loss is lower than the rectangular shaped nano-grating structure, but higher than the triangular shaped nano-grating structure. This analysis confirmed that the triangular shaped nano-gratings are an excellent alternative AR coating for conversion efficiency improvement in GaAs solar cells.
- Authors: Das, Narottam , Islam, Syed
- Date: 2016
- Type: Text , Journal article
- Relation: Energies Vol. 9, no. 9 (2016), p. 1-13
- Full Text:
- Reviewed:
- Description: This paper presents the design and analysis of nano-structured gratings to improve the conversion efficiency in GaAs solar cells by reducing the light reflection losses. A finite-difference time domain (FDTD) simulation tool is used to design and simulate the light reflection losses of the subwavelength grating (SWG) structure in GaAs solar cells. The SWG structures perform as an excellent alternative antireflective (AR) coating due to their capacity to reduce the reflection losses in GaAs solar cells. It allows the gradual change in the refractive index that confirms an excellent AR and the light trapping properties, when compared with the planar thin film structures. The nano-rod structure performs as a single layer AR coating, whereas the triangular (i.e., conical or perfect cone) and parabolic (i.e., trapezoidal/truncated cone) shaped nano-grating structures perform as a multilayer AR coating. The simulation results confirm that the reflection loss of triangular-shaped nano-grating structures having a 300-nm grating height and a 830-nm period is about 2%, which is about 28% less than the flat type substrates. It also found that the intermediate (i.e., trapezoidal and parabolic)-shaped structures, the light reflection loss is lower than the rectangular shaped nano-grating structure, but higher than the triangular shaped nano-grating structure. This analysis confirmed that the triangular shaped nano-gratings are an excellent alternative AR coating for conversion efficiency improvement in GaAs solar cells.
Diagnosing transformer winding deformation faults based on the analysis of binary image obtained from FRA signature
- Zhao, Zhongyong, Yao, Chenguo, Tang, Chao, Li, Chengxiang, Yan, Fayou, Islam, Syed
- Authors: Zhao, Zhongyong , Yao, Chenguo , Tang, Chao , Li, Chengxiang , Yan, Fayou , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 40463-40474
- Full Text:
- Reviewed:
- Description: Frequency response analysis (FRA) has been widely accepted as a diagnostic tool for power transformer winding deformation faults. Typically, both amplitude-frequency and phase-frequency signatures are obtained by an FRA analyzer. However, most existing FRA analyzers use only the information on amplitude-frequency signature, while phase-frequency information is neglected. It is also found that in some cases, the diagnostic results obtained by FRA amplitude-frequency signatures do not comply with some hard evidence. This paper introduces a winding deformation diagnostic method based on the analysis of binary images obtained from FRA signatures to improve FRA outcomes. The digital image processing technique is used to process the binary image and obtain a diagnostic indicator, to arrive at an outcome for interpreting winding faults with improved accuracy.
- Authors: Zhao, Zhongyong , Yao, Chenguo , Tang, Chao , Li, Chengxiang , Yan, Fayou , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 40463-40474
- Full Text:
- Reviewed:
- Description: Frequency response analysis (FRA) has been widely accepted as a diagnostic tool for power transformer winding deformation faults. Typically, both amplitude-frequency and phase-frequency signatures are obtained by an FRA analyzer. However, most existing FRA analyzers use only the information on amplitude-frequency signature, while phase-frequency information is neglected. It is also found that in some cases, the diagnostic results obtained by FRA amplitude-frequency signatures do not comply with some hard evidence. This paper introduces a winding deformation diagnostic method based on the analysis of binary images obtained from FRA signatures to improve FRA outcomes. The digital image processing technique is used to process the binary image and obtain a diagnostic indicator, to arrive at an outcome for interpreting winding faults with improved accuracy.
Disconnection of single-phase rooftop PVs after short-circuit faults in residential feeders
- Yengejeh, Hadi, Shahnia, Farhad, Islam, Syed
- Authors: Yengejeh, Hadi , Shahnia, Farhad , Islam, Syed
- Date: 2016
- Type: Text , Journal article
- Relation: Australian Journal of Electrical and Electronics Engineering Vol. 13, no. 2 (2016), p. 151-165
- Full Text:
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- Description: This paper presents an analysis on the disconnection time of single-phase rooftop photovoltaic systems (PVs), located in a three-phase four-wire low voltage distribution feeder, after a single-phase and a three-phase short-circuit fault on the low-voltage feeder. The paper aims to evaluate and discuss the disconnection time and disconnection sequence of PVs in a network with 100% PV penetration level to evaluate the islanding issues that are related to the safety of people and the damage of electrical apparatus. The impact of different parameters such as the location of the fault, impedance of the fault and the ratio of PVs generation capacity to the load demand are contemplated in the analysis. Furthermore, the influence of the network earthing in the form of multiple earthed neutral and non-effectively grounded systems are evaluated on the PVs disconnection time. This research intends to figure out the conditions under which the PVs in the feeder may fail to disconnect after a single-phase or three-phase fault and continue to feed the fault.
- Authors: Yengejeh, Hadi , Shahnia, Farhad , Islam, Syed
- Date: 2016
- Type: Text , Journal article
- Relation: Australian Journal of Electrical and Electronics Engineering Vol. 13, no. 2 (2016), p. 151-165
- Full Text:
- Reviewed:
- Description: This paper presents an analysis on the disconnection time of single-phase rooftop photovoltaic systems (PVs), located in a three-phase four-wire low voltage distribution feeder, after a single-phase and a three-phase short-circuit fault on the low-voltage feeder. The paper aims to evaluate and discuss the disconnection time and disconnection sequence of PVs in a network with 100% PV penetration level to evaluate the islanding issues that are related to the safety of people and the damage of electrical apparatus. The impact of different parameters such as the location of the fault, impedance of the fault and the ratio of PVs generation capacity to the load demand are contemplated in the analysis. Furthermore, the influence of the network earthing in the form of multiple earthed neutral and non-effectively grounded systems are evaluated on the PVs disconnection time. This research intends to figure out the conditions under which the PVs in the feeder may fail to disconnect after a single-phase or three-phase fault and continue to feed the fault.
Disconnection time and sequence of rooftop PVs under short-circuit faults in low voltage networks
- Yengejeh, Hadi, Shahnia, Farhad, Islam, Syed
- Authors: Yengejeh, Hadi , Shahnia, Farhad , Islam, Syed
- Date: 2015
- Type: Text , Conference proceedings , Conference paper
- Relation: North American Power Symposium, NAPS 2015; Charlotte, United States; 4th-6th October 2015 p. 1-6
- Full Text:
- Reviewed:
- Description: This paper presents an analysis on the disconnection time of single-phase rooftop PVs, located in a three-phase four-wire low voltage distribution feeder after a line-to-ground short-circuit fault on the low voltage feeder. The paper aims to evaluate and discuss the disconnection time and sequence of PVs in a network with 100% PV penetration level. The impact of different parameters such as the location of the fault, impedance of the fault and the ratio of PVs generation capacity to the load demand are considered. Furthermore, the effect of the system earthing in the form of multiple earthed neutral and non-effectively grounded systems are evaluated on the PVs disconnection time. The analyses intend to figure out the conditions under which the PVs in the feeder may fail to disconnect after a line-to-ground fault and keep feeding the fault. The analyses are carried out in PSCAD/EMTDC software.
- Authors: Yengejeh, Hadi , Shahnia, Farhad , Islam, Syed
- Date: 2015
- Type: Text , Conference proceedings , Conference paper
- Relation: North American Power Symposium, NAPS 2015; Charlotte, United States; 4th-6th October 2015 p. 1-6
- Full Text:
- Reviewed:
- Description: This paper presents an analysis on the disconnection time of single-phase rooftop PVs, located in a three-phase four-wire low voltage distribution feeder after a line-to-ground short-circuit fault on the low voltage feeder. The paper aims to evaluate and discuss the disconnection time and sequence of PVs in a network with 100% PV penetration level. The impact of different parameters such as the location of the fault, impedance of the fault and the ratio of PVs generation capacity to the load demand are considered. Furthermore, the effect of the system earthing in the form of multiple earthed neutral and non-effectively grounded systems are evaluated on the PVs disconnection time. The analyses intend to figure out the conditions under which the PVs in the feeder may fail to disconnect after a line-to-ground fault and keep feeding the fault. The analyses are carried out in PSCAD/EMTDC software.
Domestic load management with coordinated photovoltaics, battery storage and electric vehicle operation
- Das, Narottam, Haque, Akramul, Zaman, Hasneen, Morsalin, Sayidul, Islam, Syed
- Authors: Das, Narottam , Haque, Akramul , Zaman, Hasneen , Morsalin, Sayidul , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 12075-12087
- Full Text:
- Reviewed:
- Description: Coordinated power demand management at residential or domestic levels allows energy participants to efficiently manage load profiles, increase energy efficiency and reduce operational cost. In this paper, a hierarchical coordination framework to optimally manage domestic load using photovoltaic (PV) units, battery-energy-storage-systems (BESs) and electric vehicles (EVs) is presented. The bidirectional power flow of EV with vehicle to grid (V2G) operation manages real-time domestic load profile and takes appropriate coordinated action using its controller when necessary. The proposed system has been applied to a real power distribution network and tested with real load patterns and load dynamics. This also includes various test scenarios and prosumer's preferences e.g., with or without EVs, number of EV owners, number of households, and prosumer's daily activities. This is a combined hybrid system for hierarchical coordination that consists of PV units, BES systems and EVs. The system performance was analyzed with different commercial EV types with charging/ discharging constraints and the result shows that the domestic load demand on the distribution grid during the peak period has been reduced significantly. In the end, this proposed system's performance was compared with the prediction-based test techniques and the financial benefits were estimated. © 2013 IEEE.
- Authors: Das, Narottam , Haque, Akramul , Zaman, Hasneen , Morsalin, Sayidul , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 12075-12087
- Full Text:
- Reviewed:
- Description: Coordinated power demand management at residential or domestic levels allows energy participants to efficiently manage load profiles, increase energy efficiency and reduce operational cost. In this paper, a hierarchical coordination framework to optimally manage domestic load using photovoltaic (PV) units, battery-energy-storage-systems (BESs) and electric vehicles (EVs) is presented. The bidirectional power flow of EV with vehicle to grid (V2G) operation manages real-time domestic load profile and takes appropriate coordinated action using its controller when necessary. The proposed system has been applied to a real power distribution network and tested with real load patterns and load dynamics. This also includes various test scenarios and prosumer's preferences e.g., with or without EVs, number of EV owners, number of households, and prosumer's daily activities. This is a combined hybrid system for hierarchical coordination that consists of PV units, BES systems and EVs. The system performance was analyzed with different commercial EV types with charging/ discharging constraints and the result shows that the domestic load demand on the distribution grid during the peak period has been reduced significantly. In the end, this proposed system's performance was compared with the prediction-based test techniques and the financial benefits were estimated. © 2013 IEEE.